Little is known about the effect of decomposer diversity on litter decomposition in alpine areas. Especially under the premise that alpine ecosystems are very sensitive to global change and are currently undergoing extensive land-use changes, a better understanding is needed to predict how environmental change will affect litter decomposition. A mesocosm experiment was conducted to compare the effects of the most common and functionally diverse invertebrates (earthworms, millipedes and sciarid larvae) found in alpine soils on decomposition rates and to assess how decomposer diversity affects litter decomposition. Experimental and estimated (i.e. projected to field decomposer-biomass) litter mass loss was 13-33% higher in the three-species treatment. Notably, the variability in decomposition was greatly reduced when decomposer diversity was high, indicating a portfolio effect. Our results suggest that invertebrate decomposer diversity is essential for sustaining litter decomposition in alpine areas and for the stability of this service.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4381298 | PMC |
http://dx.doi.org/10.1016/j.soilbio.2015.01.026 | DOI Listing |
Environ Microbiol
January 2025
Department of Biochemistry, Genetics and Microbiology, Centre for Microbial Ecology and Genomics, University of Pretoria, Pretoria, South Africa.
Plant detritus is abundant in grasslands but decomposes slowly and is relatively nutrient-poor, whereas animal carcasses are labile and nutrient-rich. Recent studies have demonstrated that labile nutrients from carcasses can significantly alter the long-term soil microbial function at an ecosystem scale. However, there is a paucity of knowledge on the functional and structural response and temporal scale of soil microbiomes beneath large herbivore carcasses.
View Article and Find Full Text PDFEvol Comput
January 2025
College of Science, Northwest A&F University, Yangling 712100, China
Decomposition-based multi-objective evolutionary algorithms (MOEAs) are popular methods utilized to address many-objective optimization problems (MaOPs). These algorithms decompose the original MaOP into several scalar optimization subproblems, and solve them to obtain a set of solutions to approximate the Pareto front (PF). The decomposition approach is an important component in them.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
Geneis Beijing Co., Ltd, Beijing, 100102, China.
The process of new drug development is complex, whereas drug-disease association (DDA) prediction aims to identify new therapeutic uses for existing medications. However, existing graph contrastive learning approaches typically rely on single-view contrastive learning, which struggle to fully capture drug-disease relationships. Subsequently, we introduce a novel multi-view contrastive learning framework, named CDPMF-DDA, which enhances the model's ability to capture drug-disease associations by incorporating diverse information representations from different views.
View Article and Find Full Text PDFISME Commun
January 2024
Key Laboratory of Marine Genetic Resources, Ministry of Natural Resources of PR China, 178 Daxue Road, Siming District, Xiamen City, Fujian Province 361005, PR China.
Transport of organic matter (OM) occurs widely in the form of animal and plant detritus in global oceans, playing a crucial role in global carbon cycling. While wood- and whale-falls have been extensively studied, the process of OM remineralization by microorganisms remains poorly understood particularly in pelagic regions on a global scale. Here, enrichment experiments with animal tissue or plant detritus were carried out in three deep seas for 4-12 months using the deep-sea incubators.
View Article and Find Full Text PDFMach Learn
October 2024
Division of Biostatistics and Health Data Science, School of Public Health, University of Minnesota, Minneapolis, 55455, MN, USA.
Data for several applications in diverse fields can be represented as multiple matrices that are linked across rows or columns. This is particularly common in molecular biomedical research, in which multiple molecular "omics" technologies may capture different feature sets (e.g.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!